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Registro Completo |
Biblioteca(s): |
Embrapa Pantanal. |
Data corrente: |
05/01/2004 |
Data da última atualização: |
27/03/2017 |
Autoria: |
SERENO, F. T. P. S.; SERENO, J. R. B.; RODRIGUEZ-GALLARDO, P.P.; VEGA-PLA, J. L.; DELGADO BERMEJO, J. V. |
Afiliação: |
Universidad de Cordoba (Espana). Embrapa Pantanal (Corumba, MS). |
Título: |
Brazilian pantaneiro horse: genetic diversity at microsatellite level. |
Ano de publicação: |
2003 |
Fonte/Imprenta: |
In: WORLD CONFERENCE ON ANIMAL PRODUCTION, 9.; REUNIAO DA ASSOCIACAO LATINOAMERICANA DE PRODUCAO ANIMAL, 18., 2003, Porto Alegre. Abstracts. Porto Alegre: [s.n.], 2003. nao paginado. CD-ROM. |
Idioma: |
Inglês |
Conteúdo: |
Brazilian Pantaneiro Horse was originated from horses introduced by Spanish and Portuguese colons about three centuries ago. This population was selected to resist the adverse conditions of the environment and now is submitted to a conservation program where DNA typing will be an important tool to help in the management and control "in situ" conservation nucleus of Embrapa Pantanal farm. An analysis of 12 microsatellite loci in 101 animals has been used to define the genetic strucuture of the Pantaneiro Horse from Brazil. Nei's DA distances from Thoroughbred, Arabian, Spanish Pure Breed (Andalusian) and Uruguay Creole horses were calculated showing a minimum distance of Pantaneiro Horse and Spanish Pure Breed (0.228) and similar distance from Spanish Pure Breed and Thoroughbred and Arabian (0.355 and 0.332). Resulta indicate a great diversity level, clear distancing respect to the other breeds and genetic uniformity inside the Pantaneiro Horse. Finally we suggest the utilisation of genetic for genealogical registers control, conservation plans and Pantaneira breed management. |
Palavras-Chave: |
Animal conservation; Cavalo pantaneiro; Conservacao animal; Equine; Marca molecular; Microsatellites; Molecular marks. |
Thesagro: |
Eqüino. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01975naa a2200265 a 4500 001 1810945 005 2017-03-27 008 2003 bl --- 0-- u #d 100 1 $aSERENO, F. T. P. S. 245 $aBrazilian pantaneiro horse$bgenetic diversity at microsatellite level. 260 $c2003 520 $aBrazilian Pantaneiro Horse was originated from horses introduced by Spanish and Portuguese colons about three centuries ago. This population was selected to resist the adverse conditions of the environment and now is submitted to a conservation program where DNA typing will be an important tool to help in the management and control "in situ" conservation nucleus of Embrapa Pantanal farm. An analysis of 12 microsatellite loci in 101 animals has been used to define the genetic strucuture of the Pantaneiro Horse from Brazil. Nei's DA distances from Thoroughbred, Arabian, Spanish Pure Breed (Andalusian) and Uruguay Creole horses were calculated showing a minimum distance of Pantaneiro Horse and Spanish Pure Breed (0.228) and similar distance from Spanish Pure Breed and Thoroughbred and Arabian (0.355 and 0.332). Resulta indicate a great diversity level, clear distancing respect to the other breeds and genetic uniformity inside the Pantaneiro Horse. Finally we suggest the utilisation of genetic for genealogical registers control, conservation plans and Pantaneira breed management. 650 $aEqüino 653 $aAnimal conservation 653 $aCavalo pantaneiro 653 $aConservacao animal 653 $aEquine 653 $aMarca molecular 653 $aMicrosatellites 653 $aMolecular marks 700 1 $aSERENO, J. R. B. 700 1 $aRODRIGUEZ-GALLARDO, P.P. 700 1 $aVEGA-PLA, J. L. 700 1 $aDELGADO BERMEJO, J. V. 773 $tIn: WORLD CONFERENCE ON ANIMAL PRODUCTION, 9.; REUNIAO DA ASSOCIACAO LATINOAMERICANA DE PRODUCAO ANIMAL, 18., 2003, Porto Alegre. Abstracts. Porto Alegre: [s.n.], 2003. nao paginado. CD-ROM.
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Registro original: |
Embrapa Pantanal (CPAP) |
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Registro Completo
Biblioteca(s): |
Embrapa Mandioca e Fruticultura; Embrapa Semiárido. |
Data corrente: |
15/10/2019 |
Data da última atualização: |
22/01/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
VITOR, A. B.; DINIZ, R. P.; MORGANTE, C. V.; ANTONIO, R. P.; OLIVEIRA, E. J. de. |
Afiliação: |
Alison Borges Vitor, Universidade Federal do Recôncavo da Bahia, Cruz das Almas, BA; Rafael Parreira Diniz, Universidade Federal do Recôncavo da Bahia, Cruz das Almas, BA; CAROLINA VIANNA MORGANTE, CPATSA; RAFAELA PRISCILA ANTONIO, CPATSA; EDER JORGE DE OLIVEIRA, CNPMF. |
Título: |
Early prediction models for cassava root yield in different water regimes. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Field Crops Research, v. 239, p. 149-158, 2019. |
DOI: |
10.1016/j.fcr.2019.05.017 |
Idioma: |
Inglês |
Conteúdo: |
The development of cassava (Manihot esculenta Crantz) varieties with greater tolerance of water deficit depends on optimized phenotyping tools. The objective of this work was to develop early prediction models of final root yield (12 months after planting - MAP) using physiological and agronomic data obtained at 4 MAP under two water regimes. Nine genotypes of cassava were evaluated under two treatments (irrigated and with water deficit), using a complete randomized block design, in a factorial scheme of 2 harvest periods (at 4 and 12 MAP) × 9 genotypes, with four replications. Both treatment groups were irrigated until 3 MAP. After this period, irrigation was interrupted for the water deficit treatment group. Fourteen physiological and agronomic traits were evaluated in all harvest periods. Four prediction models were evaluated: linear regression with stepwise selection (LRSS), linear regression with backward selection (LRBS), Bayesian ridge regression (BRR), and partial least squares (PLS). Most of the models presented a high predictive ability for final root yield (R2 ranging from 0.83 to 0.91). However, in all prediction scenarios, the PLS model presented a high R2 (0.84 to 0.91) associated with the lowest root-mean-square error (RMSE) (0.82 to 1.60). Differences in the predictive ability of the models may have occurred due to the relative importance of the early traits. In the case of PLS, the most important traits for the model were stomatal conductance, root yield at 4 MAP, leaf area index and number of roots. Regardless of the water condition, the physiological and agronomic data collected at an early stage could successfully be used to predict the final root yield with great efficiency. This strategy can reduce the cost of phenotyping, increasing the capacity for analysis and optimization of genetic gains for tolerance to drought in cassava. MenosThe development of cassava (Manihot esculenta Crantz) varieties with greater tolerance of water deficit depends on optimized phenotyping tools. The objective of this work was to develop early prediction models of final root yield (12 months after planting - MAP) using physiological and agronomic data obtained at 4 MAP under two water regimes. Nine genotypes of cassava were evaluated under two treatments (irrigated and with water deficit), using a complete randomized block design, in a factorial scheme of 2 harvest periods (at 4 and 12 MAP) × 9 genotypes, with four replications. Both treatment groups were irrigated until 3 MAP. After this period, irrigation was interrupted for the water deficit treatment group. Fourteen physiological and agronomic traits were evaluated in all harvest periods. Four prediction models were evaluated: linear regression with stepwise selection (LRSS), linear regression with backward selection (LRBS), Bayesian ridge regression (BRR), and partial least squares (PLS). Most of the models presented a high predictive ability for final root yield (R2 ranging from 0.83 to 0.91). However, in all prediction scenarios, the PLS model presented a high R2 (0.84 to 0.91) associated with the lowest root-mean-square error (RMSE) (0.82 to 1.60). Differences in the predictive ability of the models may have occurred due to the relative importance of the early traits. In the case of PLS, the most important traits for the model were stomatal conductance, root yield at ... Mostrar Tudo |
Palavras-Chave: |
Défic hídrico; Fenotipagem; Raízes de mandioca. |
Thesagro: |
Fisiologia; Mandioca; Manihot Esculenta. |
Thesaurus NAL: |
Cassava; Physiology; Plant breeding. |
Categoria do assunto: |
-- G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/205097/1/Early-prediction-models-for-cassava-2019.pdf
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Marc: |
LEADER 02688naa a2200289 a 4500 001 2114761 005 2020-01-22 008 2019 bl uuuu u00u1 u #d 024 7 $a10.1016/j.fcr.2019.05.017$2DOI 100 1 $aVITOR, A. B. 245 $aEarly prediction models for cassava root yield in different water regimes.$h[electronic resource] 260 $c2019 520 $aThe development of cassava (Manihot esculenta Crantz) varieties with greater tolerance of water deficit depends on optimized phenotyping tools. The objective of this work was to develop early prediction models of final root yield (12 months after planting - MAP) using physiological and agronomic data obtained at 4 MAP under two water regimes. Nine genotypes of cassava were evaluated under two treatments (irrigated and with water deficit), using a complete randomized block design, in a factorial scheme of 2 harvest periods (at 4 and 12 MAP) × 9 genotypes, with four replications. Both treatment groups were irrigated until 3 MAP. After this period, irrigation was interrupted for the water deficit treatment group. Fourteen physiological and agronomic traits were evaluated in all harvest periods. Four prediction models were evaluated: linear regression with stepwise selection (LRSS), linear regression with backward selection (LRBS), Bayesian ridge regression (BRR), and partial least squares (PLS). Most of the models presented a high predictive ability for final root yield (R2 ranging from 0.83 to 0.91). However, in all prediction scenarios, the PLS model presented a high R2 (0.84 to 0.91) associated with the lowest root-mean-square error (RMSE) (0.82 to 1.60). Differences in the predictive ability of the models may have occurred due to the relative importance of the early traits. In the case of PLS, the most important traits for the model were stomatal conductance, root yield at 4 MAP, leaf area index and number of roots. Regardless of the water condition, the physiological and agronomic data collected at an early stage could successfully be used to predict the final root yield with great efficiency. This strategy can reduce the cost of phenotyping, increasing the capacity for analysis and optimization of genetic gains for tolerance to drought in cassava. 650 $aCassava 650 $aPhysiology 650 $aPlant breeding 650 $aFisiologia 650 $aMandioca 650 $aManihot Esculenta 653 $aDéfic hídrico 653 $aFenotipagem 653 $aRaízes de mandioca 700 1 $aDINIZ, R. P. 700 1 $aMORGANTE, C. V. 700 1 $aANTONIO, R. P. 700 1 $aOLIVEIRA, E. J. de 773 $tField Crops Research$gv. 239, p. 149-158, 2019.
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Embrapa Semiárido (CPATSA) |
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